Validation involves the comparison of experimental data with simulation outputs and is the focus of this work. Errors in simulation predictions may be assessed in this way. Validation requires highly-detailed data and description to accompany these data, and uncertainties are very important.

The purpose of this work is to provide highly complete validation data to assess the accuracy of CFD simulations. This aim is fundamentally different from the typical discovery experiments common in research. The measurement of these physics was not necessarily original but performed with modern, high fidelity methods. Data were tabulated through an online database for direct use in Reynolds-Averaged Navier Stokes simulations. Detailed instrumentation and documentation were used to make the data more useful for validation. This work fills the validation data gap for steady and transient mixed convection.

The physics in this study included mixed convection on a vertical flat plate. Mixed convection is a condition where both forced and natural convection influence fluid momentum and heat transfer phenomena. Flow was forced over a vertical flat plate in a facility built for validation experiments. Thermal and velocity data were acquired for steady and transient flow conditions. The steady case included both buoyancy-aided and buoyancy-opposed mixed convection while the transient case was for buoyancy-opposed flow. The transient was a ramp-down flow transient, and results were ensemble-averaged for improved statistics. Uncertainty quantification was performed on all results with bias and random sources.

An independent method of measuring heat flux was devised to assess the accuracy of commercial heat flux sensors used in the heated wall. It measured the convective heat flux by the temperature gradient in air very near the plate surface. Its accuracy was assessed by error estimations and uncertainty quantification.

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Blake W. LanceRefined climate downscaling for the Intermountain Westhttp://digitalcommons.usu.edu/all_datasets/7
http://digitalcommons.usu.edu/all_datasets/7Wed, 17 Dec 2014 10:02:03 PST
Large biases associated with climate projections are problematic when it comes to their regional application in the assessment of water resources and ecosystems. We produced a set of regional climate projections that have the systematic biases reduced. The dataset first utilized a statistical regression technique and a global reanalysis dataset to correct biases in the globally-simulated variables that are subsequently used to drive the regional model. The bias-corrected global simulation data led to a more realistic regional climate simulation of precipitation and associated atmospheric dynamics, as well as snow water equivalent (SWE) in comparison to the original globally-driven simulation. This effective and economical method provides a useful tool to reduce biases in regional climate downscaling simulations of water resource variables.
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Robert Gillies et al.Grazing Exclosure Experiment on the Henry Mountains of Southern Utahhttp://digitalcommons.usu.edu/all_datasets/6
http://digitalcommons.usu.edu/all_datasets/6Mon, 08 Dec 2014 15:15:11 PST
The data contained herein are the results of a grazing exclosure experiment on the Henry Mountains of S. Utah [38°5’ N, 100°50’W] to determine the relative impacts of bison, cattle, and lagomorphs on forage availability. Exclosures were erected in October 2011 and the standing crop of grass inside both exclosure types (full and partial), as well as an open reference plot was clipped in October 2012. Additionally, the local ranching community was surveyed to measure their perceptions of the bison – cattle conflict in the Henry Mountains.
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Johan du Toit et al.Genotyping-by-Sequencing for Populus Population Genomics: An Assessment of Genome Sampling Patterns and Filtering Approacheshttp://digitalcommons.usu.edu/all_datasets/5
http://digitalcommons.usu.edu/all_datasets/5Thu, 04 Dec 2014 14:15:10 PST
Continuing advances in nucleotide sequencing technology are inspiring a suite of genomic approaches in studies of natural populations. Researchers are faced with data management and analytical scales that are increasing by orders of magnitude. With such dramatic advances comes a need to understand biases and error rates, which can be propagated and magnified in large-scale data acquisition and processing. Here we assess genomic sampling biases and the effects of various population-level data filtering strategies in a genotyping-by-sequencing (GBS) protocol. We focus on data from two species of Populus, because this genus has a relatively small genome and is emerging as a target for population genomic studies. We estimate the proportions and patterns of genomic sampling by examining the Populus trichocarpa genome (Nisqually-1), and demonstrate a pronounced bias towards coding regions when using the methylation-sensitive ApeKI restriction enzyme in this species. Using population-level data from a closely related species (P. tremuloides), we also investigate various approaches for filtering GBS data to retain high-depth, informative SNPs that can be used for population genetic analyses. We find a data filter that includes the designation of ambiguous alleles resulted in metrics of population structure and Hardy-Weinberg equilibrium that were most consistent with previous studies of the same populations based on other genetic markers. Analyses of the filtered data (27,910 SNPs) also resulted in patterns of heterozygosity and population structure similar to a previous study using microsatellites. Our application demonstrates that technically and analytically simple approaches can readily be developed for population genomics of natural populations.
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Paul G. Wolf et al.Further Examination of the Geographic Range of Eriogonum corymbosum var. nilesii (Polygonaceae)http://digitalcommons.usu.edu/all_datasets/3
http://digitalcommons.usu.edu/all_datasets/3Mon, 10 Nov 2014 14:49:41 PST
The buckwheat Eriogonum corymbosum is widely distributed throughout the southwestern United States, forming a complex of eight varieties. Eriogonum corymbosum var. nilesii is a primarily yellow-flowered taxon reported only from Clark County, Nevada. A previous genetic study by our research group found that variety nilesii is genetically distinct from other E. corymbosum varieties, based on a limited number of populations. Here, we assess genetic variation in 14 newly sampled yellow-flowered populations from southern Nevada, southern Utah, and northern Arizona, and compare them to genetic variation in six populations of previously determined E. corymbosum varieties. Of the new populations, we identified four as variety nilesii, four as variety aureum, three as variety glutinosum, two as apparent hybrids involving varieties aureum and nilesii, and one as a more distantly related admixture. Our results extend the range and area of E. corymbosum var. nilesii considerably. However, this extended range is confined to the Mojave Desert region of southern Nevada, and the number of known populations remains limited.
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Mark W. Ellis et al.Sweeping Langmuir Probe (SLP) of the STORMs Sounding Rocket Missionhttp://digitalcommons.usu.edu/all_datasets/2
http://digitalcommons.usu.edu/all_datasets/2Tue, 23 Sep 2014 13:33:21 PDT
On October 30, 2007 NASA launched rocket 36.218 carrying the mission: “Investigation of Mid Latitude Ionospheric Irregularities Associated with Terrestrial Weather Systems” also known as the STORMS Mission. The rocket was launched from Wallops Island, Virginia (37.95◦ N, 284.53◦ E, 67.5◦ dip angle) at twelve minutes past local midnight. It flew along an azimuth of 114◦ and reached apogee near 394 km. The rocket payload had a suite of instruments from Utah State University/Space Dynamic Lab (USU/SDL) and University of Texas, Dallas (UTD), for making in-situ electron density, wind and electric field measurements.

The Sweeping Langmuir Probe or SLP was one of the instruments of the rocket payload and built by Utah State University. It operated in 2 modes: (1) Fixed mode, during which the bias voltage to the instrument was fixed at 3V , (2) Sweeping mode, during which the bias voltage applied to the probe was swept through a voltage range periodically. There was 19 such sweeps made by the instrument through the entire trajectory of the rocket and during each of these 19 sweeps the bias voltage was swept from -1V to 3 V in 1024 steps.

In this workbook, we present the current collected by the SLP during each of the 19 sweeps. The voltage measured by one of the four floating potential probes (FPP) is also included along with bias voltage and SLP current to aid in data analysis of the SLP current.

Each sheet of the workbook contains data from one of 19 sweeps of SLP.

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Padmashri Suresh et al.MetaCom: Automated Data Processing and Analysis of Metagenomic Community Sequenceshttp://digitalcommons.usu.edu/all_datasets/1
http://digitalcommons.usu.edu/all_datasets/1Thu, 06 Jun 2013 08:49:41 PDT
Advances in next generation sequencing technology have allowed metagenomic researchers to study the composition of bacterial communities through analysis of the vast numbers of sequence reads that these technologies generate. It is not feasible to analyze and interpret this large amount of data manually and individual research groups must create automated scripts and programs to analyze this data. Here, we present MetaCom, a program that offers a common set of analysis and organizational tools that can be used by research groups in the analysis of environmental samples. MetaCom is an open-source software tool that can process next generation sequencing output, identify the species present in the sample, organize the results of the analysis in an easy to manipulate format, and can calculate useful metrics of data quality.
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Cody A. Tramp et al.